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We developed the AI canvas to help you navigate the complexities of AI implementation
The AI Canvas is a strategic toolkit developed by the business and engineering minds at Merantix Labs and University of St. Gallen to guide companies through AI project implementation and sustainable deployment.
The novelty of many AI applications presents challenges to many companies who are not able to scale. With our comprehensive framework, we look into the topics of business, technology, organization, and AI Lifecycle.
Value Proposition
One of the first points we consider is the value proposition. What value can AI bring to your company? Why should you develop AI solutions and/or strategy?
The AI canvas' value proposition provides a unique combination of products and services, which bring value to the user while considering possible partnerships.
The AI canvas' value proposition provides a unique combination of products and services, which bring value to the user while considering possible partnerships.
Performance Indicators
A crucial part of assessing AI topics is understanding the necessary investments, both financial and non-financial, as well as expected returns in the short and long-term.
Organization
AI is the next disruptive general technology and as such requires a novel approach to leading and operating organizations. Therefore, to build an AI-native company, the leadership has to think about what organizational setup is most conducive to AI development, who makes decisions about AI projects and infrastructure, and what types of new roles are necessary.
Data & Technology
Data and technology are the main enabling factors for applying AI. Over the last decade, numerous new frameworks and tools have been developed to facilitate the application of AI as well as the governance of data. Choosing the right framework and organizational setting early on guarantees success in the long run.
Operational Implication
The novelty of many AI applications together with the inherently indeterminate nature presents a multitude of challenges for deploying them to production. It is important for any AI-ready company to address issues such as governance & compliance, regulation, safety and security.
AI Lifecycle
A defining characteristic of AI systems is their dynamic nature. Changes in the underlying data distribution, business metric or organizational setup will require a re-evaluation of the technology and models. As such, AI products undergo a life cycle that connects all parts of the AI canvas. The AI lifecycle should be kept in mind along the whole process of AI implementation.
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